code: def test_oss_fit_resample():
      oss = OneSidedSelection(random_state=RND_SEED)
      X_resampled, y_resampled = oss.fit_resample(X, Y)
  
      X_gt = np.array(
          [
              [-0.3879569, 0.6894251],
              [0.91542919, -0.65453327],
              [-0.65571327, 0.42412021],
              [1.06446472, -1.09279772],
              [0.30543283, -0.02589502],
              [-0.00717161, 0.00318087],
              [-0.09322739, 1.28177189],
              [-0.77740357, 0.74097941],
              [-0.43877303, 1.07366684],
              [-0.85795321, 0.82980738],
              [-0.30126957, -0.66268378],
              [0.20246714, -0.34727125],
          ]
      )
      y_gt = np.array([0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1])
      assert_array_equal(X_resampled, X_gt)
      assert_array_equal(y_resampled, y_gt)
  
file_path: imbalanced-learn/imblearn/under_sampling/_prototype_selection/tests/test_one_sided_selection.py
imports: import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.utils._testing import assert_array_equal
  from imblearn.under_sampling import OneSidedSelection
label_desc: Use image node_id 2 for calling a global function with example usage: test_oss_fit_resample() without return types